About this episode
Interpreting complicated models is a hot topic. How can we trust and manage AI models that we can’t explain? In this episode, Janis Klaise, a data scientist with Seldon, joins us to talk about model interpretation and Seldon’s new open source project called Alibi . Janis also gives some of his thoughts on production ML/AI and how Seldon addresses related problems. Join the discussion Changelog++ members support our work, get closer to the metal, and make the ads disappear. Join today! Sponsors: DigitalOcean – Check out DigitalOcean’s dedicated vCPU Droplets with dedicated vCPU threads. Get started for free with a $50 credit. Learn more at do.co/changelog . DataEngPodcast – A podcast about data engineering and modern data infrastructure. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com . Featuring: Janis Klaise – GitHub , LinkedIn , X Chris Benson – Website , GitHub , LinkedIn , X Daniel Whitenack – Website , GitHub , X Show Notes: Seldon Seldon Core Alibi Books “The Foundation Series” by Isaac Asimov “Interpretable Machine Learning” by Christoph Molnar Something missing or broken? PRs welcome!